improvement power system dynamic stability by using upfc

Tabriz Journal of Electrical Engineering (TJEE), vol. 51, no. 2, summer 2021 Serial no. 96

Improvement Power System Dynamic Stability

by Using UPFC with Practical Constraints

M. Maleki rizi1; S. Abazari2,*; N. Mahdian3

1- Department of Engineering, Shahrekord University, Shahrekord, Iran.

2- Department of Engineering, Shahrekord University, Shahrekord, Iran, Email: [email protected]

3- Shahid Rajaie Teacher Training University, Tehran, Iran

*Corresponding Author

Received: 2020-07-26

Revised: 2020-12-15

Accepted: 2021-02-13

Abstract This paper presents enhancement of power system dynamic stability by using unified power flow controller with assuming several real conditions and practical power system constraints. In control method design, we used all four

UPFC basic controllers simultaneously with reducing conflict of them by compromising between its control variables.

Optimization problem have been used with regarding some constraints of the system and unified power flow controller.

Particle swarm optimization algorithm has used to optimize power oscillation damping based on unified power flow

controller with an objective function. Simulation results in several multi-machine test power systems demonstrate the

capability of applied control system with regarding many constraints and limits of power system and UPFC in different

scenarios.

Keywords: Dynamic stability, unified power flow controller, practical constraints, optimization, multi-machine power

system.

1. Introduction

Electric power demand increase, bounds the power

systems to stress conditions, and leads to undesirable

system parameters. To have secure operation of power

systems, damping of power system oscillations have

attracted a great deal of attention in power-system

stability studies. New FACTS devices can be effective in

controlling power flow and damping power system

oscillations and may use to increase power system

operation's flexibility and controllability, to enhance

system stability and to achieve better utilization of

existing power systems. UPFC is the most important and

comprehensive device and has capability of regulating

active and reactive power flow and stability improvement

in power system. UPFC consists of two converters

coupled through a common DC link large capacitor.

UPFC is able to control, selectively or simultaneously,

transmission network bus-voltage, line impendence or

alternatively, the real and reactive power flow in the line

by means of series voltage-vector injection. The UPFC

can also provide controllable shunt reactive

compensation independently. These duties fulfil with to

converter voltage magnitude and phase angle control that

commonly used PI control.

In inter-area modes, PSS may not produce enough

damping, But UPFC is as an interesting approach to help

to overcome several power system operating difficulties

and controlling voltages at critical buses, transient

stabilization and small signal and dynamic control and

consequently the overall stability of power systems [1].

UPFC employing a feedback supplementary controller

can not only considerably enhance system. It can enhance

damping effect in inter-area oscillations and thus these

are advantageous over PSSs [2]. Damping effect of

UPFC based POD with PSS have compared and better

result of UPFC based one is resulted too [3]. To

investigate UPFC damping effect, LQR and UPFC

control effects on dynamic stability improvement in

SMIB had compared [4]. A fuzzy method had used to

tune series inverter PI controllers in two-area power

system and tended to decrease in oscillation of active

power [5]. PSO technique have been used in two PI

tanning of UPFC in three-machine power system, to

reduce settling time too [6]. To UPFC POD controller

design in MMPS, in three-machine system, with

selecting damping ratio based objective function LQR

have used under different loading condition and better

result demonstrated [7]. Many researchers use PSO for

this application and some of them used adaptive PSO to

improve damping controller results in compare with

standard PSO and some other previous PSO types[1].

IGWO had compared with DE and PSO to optimize

UPFC POD controller with ITAE criteria too and

demonstrated stability enhancement of MMPS in three-

machine system while comparing using only 𝑚𝐵 or 𝛿𝐸

[8]. Several researches have tried to use improved

approaches of PSO to enhance oscillation damping of

power system such as [9], which try to optimize system

energy function using UPFC while only using two basic

controllers of UPFC in three-machine reduced power

system model. Already Comparison and Assessment of

Conventional and Optimal Coordinated PSS and UPFC

Damping Controller for SMIB system in SIMULINK

platform, regarding overshoot and settling time simulated


256

[10]. And stability enhancement of a three machine

system by using the coordinated application of the UPFC

and the PSS designed by using the Firefly algorithm and

was compared with Genetic search algorithm approach

too [11]. Synchronized use of PSS along with UPFC can

result in further improvement in reliability,

controllability and mitigation of power system

oscillations thus further improving the system stability.

using the evolutionary Cuckoo algorithm technique for

transient stability enhancement of two machine power

system, through coordinated design of SS and UPFC in

SIMULINK platform had examined too[12]. Recently

researchers, try to use some of nonlinear control methods

to control UPFC in single or multi machines power

system so in [13] we can see using multi input back

stepping in multi-machine power system equipped with

UPFC oscillation damping control.

In most previous researches to investigate UPFC

dynamic stability enhancement, they have not used all

basic controllers together and simultaneously and they

have not considered any practical limitation of power

network in these regulators adjustment too. If we don’t

consider the network limitations, it is possible that in

spite of achieving good damping and dynamic result, in

real condition we can’t use UPFC in those conditions,

because some limitations such as line thermal limits can

cause damage to system or instability in real conditions. Here, beside of using optimized POD controller with

Particle Swarm Optimization (PSO) algorithm, we have

used model of UPFC in multi-machine power system

(MMPS) to investigate dynamic stability with regarding

many constraints of power system such as line

transmission capacity limits in both steady state UPFC

calculations and small signal oscillations. Another

important constraint which we assumed while adjusting

power flow in line is rating limits of the UPFC because

in real condition the rating of devices and economic

conditions seriously limits these ratings. We will deal

with UPFC in the following section.

In many of those researches multi machine system only

simulated by SIMULINK and multi machine study

restricted only to three- machine or two-area system.

In the next section UPFC introduced. In section 3 and

4 basic control and supplementary control of UPFC

presented. After introducing PSO in section 5, in section

6 steady state and dynamic equations of power system

with UPFC installed described. Finally in section 7

results of this study demonstrated.

2. Unified power flow controller

The UPFC consists of a boosting transformer and an

excitation transformer linked by two back-to-back

converters. Figure 1 shows UPFC in power system.

Equation 1 expresses the UPFC terminals voltage

relation with dc link voltage and UPFC parameters.

��𝑬 =𝒎𝑬𝑽𝒅𝒄

𝟐𝒆𝒋𝜹𝑬 , ��𝑩 =

𝒎𝑩𝑽𝒅𝒄

𝟐𝒆𝒋𝜹𝑩 (1)

The series branch of the UPFC injects an AC voltage,

Where, mB is pulse width modulation of series

(boosting) converter. By 𝑚𝐵 controlling, the magnitude

of series injected voltage can be control. 𝑚𝐸 is pulse

width modulation of shunt (exciting) inverter. By 𝑚𝐸

controlling, the output voltage of the shunt converter is

controlling. 𝛿𝐵 is phase angle of series injected voltage.

𝛿𝐸 is voltage phase angle of the shunt inverter.

𝐾𝑤

𝑠𝑇𝑤

1 + 𝑠𝑇𝑤(1 + 𝑠𝑇1

1 + 𝑠𝑇2)(

1 + 𝑠𝑇3

1 + 𝑠𝑇4)

Fig. 1. UPFC in power system

with controllable magnitude and phase angle at the power

frequency [2]. And then can exchange real and reactive

power with installed line. The shunt converter has used

primarily to provide active power demand of the series

converter through a common DC link and can exchange

reactive power to adjust voltage of bus, which is

connected. Then UPFC is a combination of STATCOM

and SSSC.

The comprehensive models of UPFC for steady state,

transient stability and dynamic stability studies and also

dynamic model of the system installed with UPFC is

presented in [14]. Wang et al have proposed a unified

model of a multi-machine power system and developed

two UPFC models, which have been linearalized and

incorporated into the Phillips-Heffron model [14]. We

have used the comprehensive UPFC model, which is

more complete for steady state analysis and applicable in

power flow solution.

3. UPFC basic control

Figure 1 shows the UPFC power and control flow

diagram. As we can see, by adjusting the magnitude and

phase angle of the shunt (exciting) converter, bus voltage

and dc voltage across common capacitor will be

controlled. Shunt active and reactive power exchange is

related with active power which series converter request

and bus voltage requirements to be kept in accepted value

respectively. Active and reactive power flow can be

controlled by adjusting magnitude and phase angle of

series converter. Wang showed that parameters of UPFC

i.e. 𝒎𝑬 , 𝒎𝑩 , 𝜹𝑬 and 𝜹𝑩 should be modulated to

achieving desired damping of oscillation too. Equations

2 to 5 express these 4 basic control functions. Wang et al

investigated the control conflict between UPFC multiple

control functions and their interactions in single-machine

infinite -bus system and showed that sometimes using all

four control function may decrease accuracy of results

[15]. Then their adjustment with attention to this

interaction is very important. We used all of these four

controllers simultaneously and have done compromise

between four control variables.


257

𝜹𝑩 = (𝟏

𝟏+𝑻𝜹𝑩𝒔) (𝑲𝑷𝒑 +

𝑲𝑷𝒊

𝒔) (𝑷𝑹𝒆𝒇 − 𝑷) (2)

𝑚𝐵 = (1

1+𝑇𝑚𝐵𝑠) (𝐾𝑄𝑝 +

𝐾𝑄𝑖

𝑠) (𝑄𝑅𝑒𝑓 − 𝑄) (3)

𝑚𝐸 = (1

1+𝑇𝑚𝐸𝑠) (𝐾𝑉𝑝 +

𝐾𝑉𝑖

𝑠) (𝑉𝑅𝑒𝑓 − 𝑉) (4)

𝛿𝐸 = (1

1+𝑇𝛿𝐸𝑠) (𝐾𝐷𝐶𝑝 +

𝐾𝐷𝐶𝑖

𝑠) (𝑉𝐷𝐶,𝑅𝑒𝑓 − 𝑉𝐷𝐶) (5)

where 𝑻𝒙 are delay time constants, and 𝑲𝒙𝒑 and 𝑲𝒙𝒊 are

PI controllers proportional and integral gains

respectively. P, Q, V and 𝑽𝑫𝑪 are active and reactive

power flow through line and bus voltage which UPFC is

connected and UPFC dc link voltage respectively.

The main practical restriction that we want to apply to

system is real and reactive power limits which UPFC can

supply without any external power supply. Due to

technical and economic restriction the rating of UPFC

power is limited and this leads to applying limits of real

and reactive power by additional limiter blocks and then

modifying the UPFC related parameters in each iteration.

4. Power oscillation damping controller based on

UPFC

Secondary control design has known as the damping

controller design, which is a supplementary control loop

that is designed to enhance transient stability of entire

electric power system. The adverse interaction between

PSS and series part control have compensated by

providing UPFC based damping controller. Thus this is

another important reason of UPFC POD controller

improvement and its application beside basic controls.

Commonly the POD controllers have a transfer

function consisting of Gain, a washout function and two

lead-lag blocks. It is showed that the UPFC based POD

controller works effectively in single machine system. To

improve its dynamic performance in a multi-machine

system, the behaviour of the controllers must be

coordinated [16]. In [17] the speed deviation is selected

and all four parameters of UPFC tried to be output of

POD. And resulted that 𝒎𝑩is the best selection. In this

paper the active power of transmission line which UPFC

controls its power flow is used as input signal and we

have used this input and output. POD controller consists

of 𝑻𝑾 wash-out time constant which selected constant

and K wash-out gain and 𝑻𝟏to 𝑻𝟒 lead-lag time constants

which should be adjust.

Fixed parameter classical controller is not suitable for

the UPFC damping control design. Then, a flexible

controller should develop. Several approaches proposed

for it, such as root locus and sensitivity analysis, pole

placement, and robust control. The conventional

techniques require heavy computation and slow

convergence. And the search methods may be trapped in

local minimum and the solution obtained may not be

optimum. In addition, it is necessary that the designed

controller provide some robustness to the variations of

parameters, conditions, and configurations. Also the

controller parameters which stabilize the system in a

certain operating condition may no longer have

acceptable results in case of large disturbances [17].

We can use an optimization problem, base on Eigen

values multi-objective function reflecting the

combination of damping factor and damping ratio is

considered as:

𝐽 = ∑ ∑ (𝜎0 − 𝜎𝑖𝑗)2

𝜎𝑖≥𝜎0

𝑁𝑃

𝑗=1

+ 𝛼 ∑ ∑ (0

− 𝑖𝑗

)2

𝑖≥0

𝑁𝑃

𝑗=1

𝒇(𝒙) = 𝐦𝐢𝐧 𝑱

max

44

min

4

max

33

min

3

max

22

min

2

max

11

min

1

maxmin

TTT

TTT

TTT

TTT

KKK

(6)

where 𝝈𝒊𝒋 are real parts of system Eigen values and 𝝈𝟎 is

desired real part of Eigen value, 𝒊𝒋

are damping ratios of

system variables and 𝟎 is desired damping ratio. Both

real part and damping ratio are important in system

stability then the objective function consists of two parts

which each part related to each of these two main factors

and α is the constant coefficient which determine the

importance weight of the two parts of the objective

function. This optimization problem can solve with one

of analytical or numerical techniques. Here we have used

PSO which introduced briefly in next section.

5. Particle swarm optimization algorithm

PSO is an optimization technique which is population-

based introduced by Kennedy and Eberhart to solve the

optimization problem with constraint. In PSO system,

multiple solutions are candidate and collaborate

simultaneously. Each candidate, called a particle, flies in

the problem search space looking to land on the optimal

position. Particles, during the generations, adjusts their

own positions according to theirs own experience and the

experience of neighbour particles. This algorithm

combines global and local search methods, and tries to

balance exploitation and exploration. In this technique

new velocity and position of each particle will be updated

according to the following equations [18]:

NikXkgbestrc

kXkpbestrckVwkV

i

iiii

,,2,1,

1

22

11

(7)

11 kVkXkX iii

(8)

where N is number of particles, k is the current iteration,

𝒘 is an inertia weight, 𝒓𝟏 and 𝒓𝟐 are random variables

between 0 and 1, 𝒄𝟏 and 𝒄𝟐are acceleration coefficients.

𝑽𝒊 and 𝑿𝒊are the velocity and position of the particle 𝒊

respectively. 𝒑𝒃𝒆𝒔𝒕𝒊 is the local best position of particle 𝒊. gbest is the global- best position of all particles.

To optimize J function that mentioned above with PSO

the lead-lag controller parameters; 𝑻𝟏 to 𝑻𝟒 and wash-

out gain K are adjusted. The UPFC modeling together

with power system have dealt in next section.

6. Modelling and control of power system with

UPFC installed


258

Figure 2 shows the UPFC in multi-machine power

system. Performance analysis and control functions

synthesis of UPFC require its steady state and dynamic

models. In order to simulate the multi-machine power

system that contains a UPFC, the UPFC have modelled

for both steady state and dynamic operations condition.

Fig. 2. UPFC in multi-machine power system

6.1. Power system with UPFC steady state model

The basic control strategy is such that the shunt

converter of the UPFC controls the UPFC bus voltage,

shunt reactive power and the dc link capacitor voltage.

The series converter controls the transmission line real

and reactive power flow. Then the steady state model

assumes that the UPFC is operating to keep real and

reactive power flows at the receiving bus and to regulate

sending bus voltage magnitude. Thus a two-source UPFC

steady-state model including source impedances has

proposed in [19].

This UPFC model is extension of the power flow

equations and, hence, it is suitable for incorporation into

an existing Newton-Raphson load flow algorithm. In this

unified solution, the UPFC state variables have adjusted

simultaneously with the nodal network state variables.

Hence, the interaction between the network and the

UPFC has taken in to account.

These steady state parameters values will use to

calculate and determine base values of UPFC control

parameters. This load flow implementation can help to

select proper placement of UPFC.

With reducing bus admittance matrices to generator

internal buses and UPFC terminal bus the following

equation can be write:

U

G

U

G

UUUG

GUGG

I

II

V

EE

YY

YYY ,,

, �� = ��

(9)

While, 𝒀𝑮𝑮 is reduced admittance matrices connecting

the generator current injection to the internal generator

voltages. 𝒀𝑮𝑼 is admittance matrices component which

gives the generator currents due to the voltages at UPFC

buses. 𝒀𝑼𝑮 is admittance matrices component which

gives UPFC currents in terms of the generator internal

voltages. 𝒀𝑼𝑼 is admittance matrices connecting UPFC

currents to the voltages at UPFC buses.��𝑮 is vector of

generator internal bus voltages. ��𝑼 is vector of UPFC ac

bus voltages. ��𝑮 is vector of generator current

injections. ��𝑼 is vector of UPFC currents injected to the

power network. Then, these parameters instant values

will incorporate in deriving matrices equation of multi

machine power system with UPFC installed which is

essential in dynamic stability analysis.

6.2. Power system linearzed model

Traditionally, for the small signal stability studies of

power system, the linear model of Phillips-Heffron has

used, and has provides reliable results [20]. Although the

model is linearized, it is enough accurate for studying low

frequency oscillations and dynamic stability of power

systems. The dynamic model of the system completely

presented in [20]. The injection model has used to

dynamic stability control of UPFC in MMPS modelling

too [4]. The nonlinear dynamic model of the system

installed with UPFC has given as (10)-(14). Equation (14)

shows the UPFC dynamics.

��𝑖 = 𝜔𝑏(𝜔𝑖 − 1)

(10)

ωi =(Pmi−Pei−Diωi)

Mi

(11) Eqi

′ =(−Eqi

′ +Efdi)

Tdoi′

(12)

Efdi =(−Efdi−Kai(VRef−Vt))

Tai

(13)

��𝐃𝐂 =𝟑𝐦𝐄

𝟒𝐂𝐝𝐜(𝐬𝐢𝐧𝛅𝐄𝐈𝐄𝐝 + 𝐜𝐨𝐬𝛅𝐄𝐈𝐄𝐪) +

𝟑𝐦𝐁

𝟒𝐂𝐝𝐜(𝐬𝐢𝐧𝛅𝐁𝐈𝐁𝐝 +

𝐜𝐨𝐬𝛅𝐁𝐈𝐁𝐪

(14)

where, i=1, 2, 3,…, n (the generators 1 to n), 𝜹𝒊 is rotor

angle of ith generator, 𝝎𝒊 is rotor speed of ith generator,

𝑷𝒎𝒊 is mechanical input power of ith generator, 𝑷𝒆𝒊 is

electrical output power of ith generator, 𝑬𝒒𝒊′ is internal

voltage behind 𝒙′ of ith generator, 𝑬𝒇𝒅𝒊 is equivalent

excitation voltage of ith generator, 𝑻𝒆𝒊 is electric torque

of ith generator, 𝑻𝒅𝒐𝒊′ is time constant of excitation circuit

of ith generator, 𝑲𝒂𝒊is regulator gain of ith generator, 𝑻𝒂𝒊

is regulator time constant of ith generator, is 𝑽𝒕𝑹𝒆𝒇𝒊 is

reference voltage of ith generator and 𝑽𝒕 is terminal

voltage. And:

𝑃𝑒 = 𝑉𝑇𝐷𝐼𝑑 + 𝑉𝑇𝑄𝐼𝑞 (15)

𝑉𝑇𝐷 = 𝑋𝑄𝐼𝑞 (16)

𝑉𝑇𝑄 = 𝐸𝑞′ − 𝑋𝐷

′𝐼𝑑 (17)

𝑉𝑇𝑖 = √𝑉𝑇𝐷𝑖2 + 𝑉𝑇𝑄𝑖

2 (18)

Where:

𝝎 = [ 𝜔1 𝜔2 … 𝜔𝑛]𝑇, 𝑬𝒒′ = [ 𝐸𝑞1

′ 𝐸𝑞2′ … 𝐸𝑞𝑛

′ ]𝑇

𝑬𝒇𝒅 = [ 𝐸𝑓𝑑1 𝐸𝑓𝑑2 … 𝐸𝑓𝑑𝑛]𝑇

𝑽𝑻𝒅 = [ 𝑉𝑑1 𝑉𝑑2 … 𝑉𝑑𝑛]𝑇 ,𝑽𝑻𝒒 = [ 𝑉𝑞1 𝑉𝑞2 … 𝑉𝑞𝑛]𝑇


259

𝑴 = 𝑑𝑖𝑎𝑔(2𝐻𝑖) , 𝑫 = 𝑑𝑖𝑎𝑔(𝐷𝑖)

𝑻𝒅𝒐′ = 𝑑𝑖𝑎𝑔(𝑇𝑑𝑜𝑖

′ ) , 𝑿𝑫 = 𝑑𝑖𝑎𝑔(𝐷𝑑𝑖)

𝑰𝒅 = [ 𝐼𝑑1 𝐼𝑑2 … 𝐼𝑑𝑛]𝑇 , 𝑰𝒒 = [ 𝐼𝑞1 𝐼𝑞2 … 𝐼𝑞𝑛]𝑇

𝐼�� = 𝐼𝑑𝑖 + 𝑗𝐼𝑞𝑖 (19)

ikik j

qkdkqk

j

qi

n

k

iki eIXXeEYI

)()2/(

1

(20)

As we can see in (9), Y is reduced admittance matrices

which contain only generators and UPFC buses. These

reduced admittance and consequently above mentioned

generators and UPFC currents represent all system power

flow. Another important practical constraint which we

have considered are limit of line thermal capacity which

can be limited by applying limits of line (𝑺𝒍𝒊𝒏𝒆,𝒍 ≤ 𝑺𝒎𝒂𝒙,𝒍 ,

𝒍 = 𝟏: 𝒏𝒍𝒊𝒏𝒆). While in each every iteration we compute

admittances, currents and powers. While we adjusting

UPFC parameters with considering these lines power

limits, we modify adjusted UPFC parameters.

Above equations can be rewritten in following matrices

form:

�� = 𝜔𝑏(𝛚 − 1) (21)

�� = 𝐌−1(𝐓𝐦 − 𝐓𝐞 − 𝐃(𝛚 − 1)) (22)

��𝐪′ = 𝐓𝐝𝐨

′ (𝐄𝐟𝐝 − 𝐄𝐪′ + (𝐗𝐝 − 𝐗𝐝

′ )𝐈𝐝) (23)

��𝐟𝐝 = (𝐊𝐀(𝐕𝐑𝐞𝐟 − 𝐕𝐭) − 𝐄𝐟𝐝)/𝐓𝐀 (24)

𝐓𝐞 = 𝐕𝐭𝐝𝐈𝐝 + 𝐕𝐐𝐈𝐭𝐪 (25)

𝑽𝒕𝒅 = 𝑿𝒒𝑰𝒒 , 𝑽𝒕𝒒 = 𝑬𝒒′ − 𝑿𝒅

′ 𝑰𝒅 (26)

With linearization above equations:

∆�� = 𝛚𝐛∆𝛚 (27)

∆�� = −𝐌−𝟏(∆𝐓𝐞 + 𝐃∆𝛚) (28)

∆��𝐪′ = 𝐓𝐝𝐨

′−𝟏(∆𝐄𝐟𝐝 − ∆𝐄𝐪′ + (𝐗𝐝 − 𝐗𝐝

′ )∆𝐈𝐝) (29)

∆��𝐟𝐝 = (𝐊𝐀(∆𝐕𝐫𝐞𝐟 − ∆𝐕𝐭) − ∆𝐄𝐟𝐝)𝐓𝐀−𝟏 (30)

∆𝐓𝐞 = ∆𝐈𝐪𝐄𝐪𝟎′ + 𝐈𝐪𝟎∆𝐄𝐪

′ + ∆𝐈𝐪(𝐗𝐪 − 𝐗𝐝′ )𝐈𝐝𝟎 + ∆𝐈𝐝(𝐗𝐪 −

𝐗𝐝′ )𝐈𝐪𝟎 (31)

∆𝐕𝐭𝐝 = 𝐗𝐪∆𝐈𝐪 , ∆𝐕𝐭𝐪 = ∆𝐄𝐪′ − 𝐗𝐝

′ ∆𝐈𝐝 (32)

Where:

(33)

(34)

(35)

BcδδBcbEcδδ

Ecedc9q87dc

ΔδKΔmKΔδK

ΔmKΔVKEΔKΔδKΔV

(36)

B

B

E

E

cdbcbcdece

m

m

KKKK

vdbA

1

AvbA

1

AvdeA

1

A5A

1

A

qdb

1

doqb

1

doqde

1

doqe

1

do

pdb

1

pb

1

pde

1

pe

1

KKTKKTKKTKKT

KTKTKTKT

KMKMKMKM

0000 (37)

Detailed values calculation of K coefficients can be find in [2]. As we can see the above equation is the standard

form of linear system as below:

∆�� = 𝑨∆𝑿 + 𝑩∆𝑼 (38)

This matrices equation is suitable for classical linear

control and numerical solving the system equations as

well as controllability analysis such as Eigen values

related techniques.

7. System simulation

7.1. Implementation algorithm

We have applied this simulation method to several

power systems and we bring results of two of them here,

first one is 39 bus new England power network and

second one is IEEE 9 bus test system. For small signal

analysis the sampling time selected 0.1 msec thus

frequency of two UPFC inverters parameters updating is

10 khz which have compliance with nowadays switches

speeds. In both two cases a power system Stabilizer

(PSS) has used only for the generator which is installed

on the slack bus. This study can be briefly described in

the following flowchart:

i. Reading power system and UPFC data;

ii. Load flow running with considering practical

limits and obtaining steady state operating point

data of system and machines;

iii. Using operating point data to calculate UPFC

parameters;

iv. Running load flow with UPFC installed

regarding constraints and then obtaining new

parameters values of system, machines and UPFC;

v. Computing linearized equations format of

whole system using previous step data and system

Eigen values;

vi. Calculating POD optimized parameters using

PSO;

vii. Small signal equations solving with all four

adjusted PI basic controllers of UPFC and adjusting

UPFC four parameters in every each iteration in all

time intervals consisting before, during and after

fault occurrence;

viii. Considering practical constraints of lines and

UPFC ratings in each every iteration and modifying

UPFC parameters and obtained powers if needed;

ix. Modifying POD parameters to new optimized

values if needed in some iteration.

7.2. The 39-Bus Power system simulation results

Figure 4 shows the studied power system which is 10-

machine 39-bus New England network. In this study, a

MATLAB program to simulate the model has used. The

result of load flow implementation is used to find UPFC

placement to improve voltage profile and load flow of

power system.

BpdbBpbEpde

Epedcpdq21e

ΔδKΔmKΔδK

ΔmKΔVKEΔKΔδKΔT

BqdbBqbEqde

Eqedcqdq34q

ΔδKΔmKΔδK

ΔmKΔVKEΔKΔδKΔE

BvdbBvbEvde

Evedcvdq65t

ΔδKΔmKΔδK

ΔmKΔVKEΔKΔδKΔV

DCDCVV

fd

q

987

vdA

1

A

1

A6A

1

A5A

1

A

qd

1

do

1

do3

1

do4

1

do

pd

1

2

11

1

1

fd

q

ΔE

EΔ

Δω

Δδ

K0K0K

KΚTΤKKT0KKΤ

ΚTΤKT0ΚΤ

ΚΜ0KMDMΚΜ

000I0

EΔ

EΔ

ωΔ

δΔ 0


260

Fig. 3. Flowchart of simulation and optimization

Fig. 4. New England power system network schematic

single line

Within load flow solution the thermal limits of lines

capacity considered. After UPFC insertion in power

network the load flow executed again. It is shown that

when UPFC is installed between two buses in the system,

the active and reactive power loses are reduced. It is also

has shown that not only the power losses are reduced, the

voltage profile of the every bus improved after

incorporate UPFC too.

For small signal and dynamic stability study we used

UPFC dynamic model and interfacing with power system

as described in 6.2. Linearized model of the multi-

machine power system consisting in UPFC, has used to

small signal analysis and damping oscillations studies.

The power rating limits of UPFC and lines capacity limits

have taken in to account during analysis. All four basic

controller of UPFC considered. Eigen values and

damping ratios of the linearized system derived and

based on these values the PSO algorithm have used to

optimize damping oscillations controller. Figure 5(a)

demonstrates the Eigen values of the system with and

without UPFC in complex plane. We can see some of

Eigen values have a little more negative real part and

smaller imaginary part. Figure 5(b) shows one machines

speed and load angle before and after inserting UPFC

which demonstrated the stabilizing impact of UPFC after

earth fault occurrence.

(a)

(b)

Fig. 5. System with and without UPFC

comparison.(a)Eigen values.(b) machine no. 5 speed

variation with and without UPFC in earth fault

occurrence

To investigate enhancement of power system stability

by a UPFC, we have studied results and responses of

these two different scenarios: (1) three phase earth fault

on the one of existing lines and (2) opening the circuit in

one of the existing lines of power system. Removing time

of both faults has selected enough small so we can use

small signal analysis and investigate dynamic stability.

But in scenario 2 it may that in several conditions due to

changing in network topology have changing in steady

state operating point, and then previous parameters can’t

be used thus should calculate new operating parameters

of UPFC and system variables values.


261

For UPFC performance analyse, two cases have

considered and applied to simulated system: (i) the

practical constraints not applied; (ii) the practical

constraints taken in to account.

7.2.1. Scenario 1: Short circuit fault

Three phase earth fault applied to line between bus 3

and 4 at 0.1 sec of simulation beginning and its duration

to clear is less than 0.1 sec which is enough short for

small signal analysis. Figure 6(a), shows the variation of

four UPFC control parameters i.e. 𝒎𝑬 , 𝒎𝑩 , 𝜹𝑬 and

𝜹𝑩 and 6(b) four output linearized control variables:

UPFC dc voltage, the UPFC installed or sending bus

voltage magnitude, active and reactive power flow in

UPFC installed line and 6(c) voltage of the bus which

UPFC installed and 6(d) voltage of the bus which fault

occurred in it and 6(e) active and 6(f) reactive power flow

which have controlled by UPFC and 6(g) four machines

speed variations before using UPFC and 6(h) same

machines speed variations after using UPFC with three

phase earth fault applied without considering practical

constraints and limits.

(a)

(b)

(c)

(d)

(e)

(f)


262

(g)

(h)

Fig.6. Damping effect of UPFC in three phase earth

fault without considering practical limits in 39-Bus

system.

Figure 7 shows the same parameters of figure 6 but

with considering practical constraints and limits

respectively.

(a)

(b)

(c)

(d)

(e)


263

(f)

(g)

Fig. 7. Damping effect of UPFC in three phase earth

fault with considering practical limits in 39-Bus system.

Figure 8 shows the effect of considering practical

constraints in 39-Bus system. 8(a) demonstrate Active

and reactive power flow in line which UPFC installed

comparing result without considering constraint and with

considering constraints and in 8(b) one machine speed

and 8(c) one machine load angle in two condition , one

with considering constraints and another without

considering constraints. As we can see in two figures 6

and 7 and with compare them, and with more contrast in

figure 8, it is observable that after fault the variation of

active and reactive power which UPFC should control is

too much and in real system we not permitted to have this

rating with multiple time of base power rating. Because

of applying these limit there are disturbances in UPFC

controlled parameters but the results are more acceptable.

And these limits consideration have not deteriorated

stability and damping of oscillations and more or less

lead to more stability.

7.2.2. Scenario 2: switch opening fault

The line switch between bus 13 and 14 has opened at

0.1 sec of simulation beginning and its duration is 0.1

sec too.

(a)

(b)

(c)

Fig. 8. Effect of practical constraints consideration in

39-Bus system

Figure 8 shows 9(a) voltage of the bus which UPFC

installed and 9(b) voltage of the bus which the line which

have opened had showed in 9(c) active and 9(d) reactive

power flow which have controlled by UPFC and 9(e) 4

machines speed variation while UPFC not used and 9(f)

four machines speed variations with UPFC and limits

applied. As we can see in this scenario the operating point

has changed. Then with controlled damping due to UPFC

effect, parameters have changed to new values without

instability.


264

(a)

(b)

(c)

7.3. The 9-Bus Power system simulation results

Figure 10 shows the 9 bus system with UPFC with

short circuit fault applying in line between bus 2 and 3 in

.1 sec after simulation and its duration is 0.1 sec. we

compared the results of system response while

considering practical constraints with them while hasn’t

considering those constraints.. As we can see in the figure

10(a), the practical constraints consideration leads to

better and faster response of UPFC power flow.

(d)

(e)

(f)

Fig. 9. Damping Effect of UPFC in line switch opening

with considering practical limits in 39-Bus system.

In Figure 10(b) and (c) the speed and load angle of one

of the machines have shown. And we can see that the

practical limits consideration leads to different variation

in speed and load angle of machines and has little

affected the damping curve of them but hasn’t deteriorate

stability of machines and system.


265

(a)

(b)

(c)

Fig. 10. Effect of practical constraints consideration in

9-Bus system

8. Conclusions

In this study, the power system with UPFC and its

main and damping controls has modeled. All of four

basic control and POD controller used simultaneously

and sometimes we found the conflict between them

during tuning of them but with compromising between

them the conflict have acceptably reduced. We applied

line transferring capacity thermal limits and UPFC active

and reactive power ratings during load flow and small

signal analyses. Applying practical constraints and limits

affected the four parameters of UPFC adjusted values, so

we have deviation in controlled parameters in particular

active and reactive power damping trends. It is important

that we hadn’t any unsafe over/under shoots in electrical

parameters which in real system not allowed and can’t

realize due to technical and economic aspects. The time

of damping power and speed oscillations and settling

may be little more while we applied those limits. In both

two scenario the limits delayed the time of damping

oscillations and omitted undesirable values, but in case

of three-phase earth fault this effects is more considerable

in compare with line opening. These limitation applying

didn’t deteriorate stability and Eigen values. This simple

method even in some changing topologies leads to

acceptable result in damping oscillation and stability

analyses.

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Appendix:

UPFC used Data:

In IEEE 9-Bus system: UPFC Rating=0.5 pu, xE=0.05

pu, xB=0.05 pu, Cdc=1 pu, Sb=100MW.

In 39-bus New England network: UPFC Rating=1.9 pu,

xE= 0.0725 pu, xB=0.0725 pu, CDC=1 pu, Sb=100MW.

improvement power system dynamic stability by using upfc

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